Coupled Monitoring and Inverse Modeling to Investigate Surface – Subsurface Hydrological and Thermal Dynamics in the Arctic Tundra

Abstract:

Quantitative characterization of the soil surface–subsurface hydrological and thermal processes is essential as they are primary factors that control the biogeochemical processes, ecological landscapes and greenhouse gas fluxes. In the Artic region, the surface–subsurface hydrological and thermal regimes co-interact and are both largely influenced by soil texture and soil organic content. In this study, we present a coupled inversion scheme that jointly inverts hydrological, thermal and geophysical data to estimate the vertical profiles of clay, sand and organic contents. Within this inversion scheme, the Community Land Model (CLM4.5) serves as a forward model to simulate the land-surface energy balance and subsurface hydrological-thermal processes. Soil electrical conductivity (from electrical resistivity tomography), temperature and water content are linked together via petrophysical and geophysical models. Particularly, the inversion scheme accounts for the influences of the soil organic and mineral content on both of the hydrological-thermal dynamics and the petrophysical relationship.

We applied the inversion scheme to the Next Generation Ecosystem Experiments (NGEE) intensive site in Barrow, AK, which is characterized by polygonal-shaped arctic tundra. The monitoring system autonomously provides a suite of above-ground measurements (e.g., precipitation, air temperature, wind speed, short-long wave radiation, canopy greenness and eddy covariance) as well as below-ground measurements (soil moisture, soil temperature, thaw layer thickness, snow thickness and soil electrical conductivity), which complement other periodic, manually collected measurements. The preliminary results indicate that the model can well reproduce the spatiotemporal dynamics of the soil temperature, and therefore, accurately predict the active layer thickness. The hydrological and thermal dynamics are closely linked to the polygon types and polygon features. The results also enable the quantification of the role of organic material in hydrological – thermal processes in the Artic region.